code: def test_huggingface_neuronx(
      sagemaker_session,
      huggingface_neuronx_latest_inference_pytorch_version,
      huggingface_neuronx_latest_inference_transformer_version,
      huggingface_neuronx_latest_inference_py_version,
  ):
      inputs = "s3://mybucket/train"
      huggingface_model = HuggingFaceModel(
          model_data=inputs,
          transformers_version=huggingface_neuronx_latest_inference_transformer_version,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          pytorch_version=huggingface_neuronx_latest_inference_pytorch_version,
          py_version=huggingface_neuronx_latest_inference_py_version,
      )
      container = huggingface_model.prepare_container_def(
          "ml.inf2.xlarge", inference_tool="neuronx"
      )
      assert container["Image"]
      assert "sdk" in container["Image"] and "py" in container["Image"]
  
file_path: sagemaker-python-sdk/tests/unit/sagemaker/huggingface/test_estimator.py
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  import pytest
  from mock import MagicMock, Mock, patch
  from sagemaker.huggingface import HuggingFace, HuggingFaceModel
  from sagemaker.session_settings import SessionSettings
  from .huggingface_utils import get_full_gpu_image_uri, GPU_INSTANCE_TYPE, REGION
label_desc: Use image node_id 7 for calling a global function with example usage: test_huggingface_neuronx(sagemaker_session, huggingface_neuronx_latest_inference_pytorch_version, huggingface_neuronx_latest_inference_transformer_version, huggingface_neuronx_latest_inference_py_version) without return types